Related Experiment Video
Updated: Sep 3, 2025

14:55
Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
Published on: January 20, 2023
3.4K
JUE Insight: COVID-19 and household preference for urban density in China
Naqun Huang1, Jindong Pang2, Yanmin Yang1
1Institute of Urban Development, Nanjing Audit University, Pukou, Nanjing, Jiangsu, 211815, China.
Summary
The COVID-19 pandemic initially lowered Chinese housing prices by 2%, but they recovered by September 2020. The pandemic also altered housing price gradients, favoring lower-density living due to health concerns.
Area of Science:
- Real Estate Economics
- Urban Economics
- Public Health
Background:
- The COVID-19 pandemic presented unprecedented challenges to global economies and social behaviors.
- Understanding its impact on housing markets is crucial for policymakers and urban planners.
- China's unique housing market dynamics provide a valuable case study.
Purpose of the Study:
- To investigate the short-term and medium-term effects of the COVID-19 outbreak on housing prices in China.
- To analyze the impact of the pandemic on housing price gradients, both horizontally and vertically.
- To identify potential shifts in household preferences driven by health risks.
Main Methods:
- Utilized transaction-level housing data from 60 Chinese cities.
- Employed a difference-in-differences (DID) specification to control for seasonal effects, specifically China's Spring Festival.
- Analyzed changes in housing price levels and spatial price variations.
Main Results:
- A 2% decrease in housing prices was observed immediately following the COVID-19 outbreak.
- Housing prices showed a gradual recovery trend, reaching pre-outbreak levels by September 2020.
- Significant flattening of the horizontal housing price gradient and a reduced price premium for high-rise buildings were noted.
- Changes in the vertical gradient within residential buildings were also identified.
Conclusions:
- COVID-19 had a temporary negative impact on Chinese housing prices.
- The pandemic induced a shift in housing preferences, favoring lower-density areas due to perceived lower infection risk.
- These shifts influenced urban spatial structures and housing market segmentation.
More Related Videos
Related Concept Videos
Bias in Epidemiological Studies
585
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
585
Pareto Chart
7.0K
A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the lines represent the cumulative total values. In this chart, the longest bars are arranged on the left and the shortest bars on the right, which makes it easier to read and interpret the data. It can also be called a Pareto diagram or Pareto analysis.
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
7.0K
Population Growth
25.7K
Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
25.7K
Sampling Plans
254
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
254
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
95
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
95
Confounding in Epidemiological Studies
251
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
251

